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Compensation Data Analytics Jobs in Utah (NOW HIRING)

Data Strategy-Manager

Salt Lake City, UT · On-site

$99K - $232K/yr

In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract ... Actual compensation within the range will be dependent upon the individual's skills, experience ...

... Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $99,000 - $232,000. Actual compensation within the range will be dependent upon the ...

... Data Analyst / ML Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $124,000 - $280,000. Actual compensation within the range will be dependent upon the ...

Analyze and improve data intake processes and optimize SparkSQL/Python workloads for performance ... Compensation The overall salary range for this role is $93,700 - $177,675. For candidates residing ...

BI - Senior Data Analyst

Orem, UT

$74K - $94K/yr

As a Senior Data Analyst, you will be responsible writing, maintaining, and evolving data pipelines ... Experience in door-to-door sales environments, solar (renewable energy) a plus Compensation ...

BI - Senior Data Analyst

Orem, UT · On-site

$70K - $80K/yr

As a Senior Data Analyst, you will be responsible writing, maintaining, and evolving data pipelines ... Experience in door-to-door sales environments, solar (renewable energy) a plus Compensation ...

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Compensation Data Analytics information

What is compensation data analytics?

Compensation data analytics is the process of collecting, analyzing, and interpreting data related to employee compensation, such as salaries, bonuses, and benefits. This field helps organizations make informed decisions about pay structures, ensure competitive and equitable compensation, and comply with legal requirements. By leveraging data analytics, companies can identify trends, address pay disparities, and optimize their compensation strategies to attract and retain top talent.

What are the key skills and qualifications needed to thrive as a Compensation Data Analytics professional, and why are they important?

To thrive as a Compensation Data Analytics professional, you need strong analytical skills, a solid understanding of compensation structures, and a degree in fields like HR, finance, or statistics. Familiarity with HR information systems (HRIS), data visualization tools like Tableau or Power BI, and proficiency in Excel or statistical software such as R or Python are commonly required. Attention to detail, problem-solving abilities, and effective communication skills help you translate complex data into actionable insights for stakeholders. These skills ensure accurate, data-driven compensation strategies that support organizational goals and fair employee practices.

What is the difference between Compensation Data Analytics vs Compensation Analyst?

AspectCompensation Data AnalyticsCompensation Analyst
CredentialsDegree in HR, Business, or Data Analytics; often certifications in data analysisDegree in HR, Business, or related field; HR certifications common
Work EnvironmentData-focused, analytical tasks, often in HR or compensation departmentsHR teams, compensation planning, employee benefits
Industry UsageUsed across industries for data-driven compensation strategiesPrimarily in HR and compensation departments within various industries
Search & Comparison IntentFocus on data analysis skills and tools for compensation dataFocus on salary structures, benefits, and employee compensation policies

Compensation Data Analytics involves analyzing large datasets to inform compensation strategies, requiring strong data skills. Compensation Analysts focus on designing and managing salary structures and benefits. Both roles collaborate but differ mainly in their focus—data analysis versus policy implementation.

What is the highest paying job in data analytics?

In data analytics, senior roles such as Data Analytics Director, Chief Data Officer, or Lead Data Scientist tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in statistical analysis, machine learning, and experience with tools like SQL, Python, or R, along with leadership responsibilities.

What jobs pay 200,000 a year in the USA?

In compensation data analytics, senior roles such as Compensation Managers, Compensation Directors, and Compensation Vice Presidents often earn $200,000 or more annually, especially with extensive experience and certifications like CCP or CBP. High-level data analysts and consultants in compensation may also reach this salary level, particularly in large organizations or consulting firms. These roles typically require advanced analytical skills, knowledge of compensation structures, and proficiency with data tools like Excel, SQL, or Tableau.

What jobs pay 500,000 a year?

In compensation data analytics, senior roles such as Chief Compensation Officer or compensation consultants with extensive experience and specialized skills can earn $500,000 or more annually. These positions often require advanced degrees, certifications, and a deep understanding of compensation strategies, market trends, and data analysis tools. High-level executive roles across various industries may also reach or exceed this salary level.

How does a Compensation Data Analytics professional typically collaborate with HR and business leaders to inform pay decisions?

Compensation Data Analytics professionals work closely with HR teams and business leaders by providing data-driven insights that guide salary structures, incentive plans, and pay equity initiatives. They interpret data from salary surveys, internal pay records, and market trends, translating complex analyses into actionable recommendations. Regular meetings and presentations are common, ensuring that stakeholders understand compensation trends and can make informed decisions that support organizational goals. Effective communication and collaboration are key, as these professionals often bridge the gap between technical analytics and strategic HR planning.

Is AI replacing data analysts?

AI is transforming the role of compensation data analysts by automating routine data processing and analysis tasks, allowing analysts to focus on strategic insights and decision-making. While AI tools can enhance efficiency, human expertise remains essential for interpreting complex data, ensuring data quality, and applying context-specific judgment. The role continues to evolve with skills in data visualization, statistical analysis, and AI tool proficiency becoming increasingly valuable.
What are popular job titles related to Compensation Data Analytics jobs in Utah? For Compensation Data Analytics jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Compensation Data Analytics jobs? Cities in Utah with the most Compensation Data Analytics job openings:
IAR Senior Data Analyst

IAR Senior Data Analyst

Western Governors University

Salt Lake City, UT • On-site

$88K - $132K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Western Governors University rating

8.6

Company rating: 8.6 out of 10

Based on 41 frontline employees who took The Breakroom Quiz

51st of 537 rated colleges and universities


Job description

If you're passionate about building a better future for individuals, communities, and our country-and you're committed to working hard to play your part in building that future-consider WGU as the next step in your career.

Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.

The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:

Grade: Professional 310Pay Range: $88,300.00 - $132,400.00

Job Description

The IAR Senior Data Analyst is responsible for extracting, processing, analyzing, and reporting on data to produce rigorous, actionable insights and research. They establish and maintain strong relationships with peers and leaders across IAR, Data Engineering, Product Management, Finance, EdTech, and Faculty staff. They perform ad hoc analyses, build standard reports and data visualizations, and deliver information and insights through various methods and media that privilege data storytelling and compress time-to-action.

Primary Responsibilities

-Drives the documentation of data and analytics needs in projects of high complexity with a student and equity-centered lens, collaborating with peers, cross-functional partners, faculty staff, and leaders. Translates of user stories into technical requirements.
-Sets and manages expectations about analytics tasks and activities through clear, timely, and effective communication with partners and stakeholders.
-Answers complex business questions requiring extensive knowledge of the university's data assets across several domains and departments.
-Identifies adequate data sources and data sets to evaluate hypotheses, build forecasts, and support findings of research projects and experiments.
-Collaborates with Data Engineering in the development of complex ETL/ELT processes and data pipelines.
-Identifies, investigates, and solves complex data issues, contributing to the accuracy, completeness, consistency, timeliness, and validity of the university's data.
-Collaborates with Data Engineering and other data & analytics partners to define standards and best practices that increase data quality across the university.
-Combines data analysis, visualization, and narrative structures to convey information in compelling ways that instigate deliberate action.
-Utilizes software, scripts, and algorithms to perform data-related tasks (e.g. importing, cleaning, transforming, analyzing, displaying) without human intervention.
-Conveys information effectively to peers, partners, and senior leaders, using a variety of resources and formats (synchronous and asynchronous, verbal and written) such as e-mails, presentations, meetings, and workshops.
-Creates and organizes information about processes, projects, operations, data assets, and insights from analyses and research, making it accessible in ways that increase the university's knowledge and efficiency.
-Writes and interprets technical documentation (e.g., Entity-Relationship, -Conceptual, Logical, and Physical data models).
-Contributes actively to the development of the university's data management platforms (e.g., data dictionaries, catalogs, etc.).
-Supports and accelerates other team members' development through constructive feedback and sharing of technical and institutional knowledge.
-Drives tasks, activities, and small-scale projects with high levels of autonomy, confidence, and collaboration with peers and partners.
-Tracks and reports own progress, dependencies, and challenges diligently. -------Breaks down complex goals into concrete tasks and activities.
-Works actively to improve own skills and knowledge through internal and external, formal and informal, structured and unstructured learning. Is a lifelong learner and embodies a growth mindset. Stays abreast of innovative developments in their area of work and plays an active role in deploying them at the university.
-Understands and abides by the relevant policies and methods to access, use, transform, store, and delete data in responsible, secure, and compliant ways.
-Collaborates effectively with other technical specialists (e.g. data engineers) in the construction of data products, systems, and applications.
-Performs other job-related duties as assigned.
Knowledge, Skills, and Abilities
-Advanced SQL proficiency, with experience writing queries and subqueries, modifying data (INSERT, UPDATE, DELETE), creating views, and knowledge of different join types, filtering, sorting, aggregation, window functions, common table expressions (CTE), and performance tuning.
-Highly proficient and experienced in using tools like Tableau and Power BI to present data and information utilizing charts, graphs, and maps, in ways that make it easy to understand trends, patterns, and outliers.
-Ability to interpret and design models that describe how data relate to one another, and to the properties of the real-world entities they represent. -Understands conceptual and logical data modeling, and has experience with dimensional models, star schema, and snowflake schema.
-Experienced with descriptive statistics, causal analysis, and inference.
-Comfortable with common project management methodologies and frameworks (e.g., Waterfall, Agile, SDLC).
-Proficient in MS Office suite, including advanced Excel knowledge.
-Proficient in flowchart and diagramming tools like Miro, Visio, Lucidchart, and similar applications.
-Familiarized with the university's most relevant KPIs, the drivers that affect them, and plays an active role in their definition and tracking.
-Ability to apply sound judgment, systems-thinking, and analytical skills to assess risks, perform root-cause analyses, make recommendations, and drive cross-functional decisions that contribute to the achievement of the university's objectives.
-Ability to perform with a very high level of autonomy, reliability, self-direction, and with a bias for action. Manages conflicting and concurrent activities with minimal need for supervision.
Minimum Qualifications
Education
Bachelor's degree in a related discipline
Experience
5 years of related experience in Data Analysis, Business Intelligence, Data Science, Statistics, Decision Intelligence, Research, Learning Science, or Behavioral/Cognitive Psychology.
Experience in lieu of education
An equivalent combination of training, experience, credentials, or accomplishments demonstrating the ability to perform the essential functions of this job may substitute for education degree requirements.
This position requires occasional travel of up to 20%, including required attendance at designated company summits (typically one to two per year). Additional travel may include conferences, visits to company locations, and other business-related events as needed. Additional travel may be assigned as needed to support business requirements.

Position & Application Details

Full-Time Regular Positions (classified as regular and working 40 standard weekly hours): This is a full-time, regular position (classified for 40 standard weekly hours) that is eligible for bonuses; medical, dental, vision, telehealth and mental healthcare; health savings account and flexible spending account; basic and voluntary life insurance; disability coverage; accident, critical illness and hospital indemnity supplemental coverages; legal and identity theft coverage; retirement savings plan; wellbeing program; discounted WGU tuition; and flexible paid time off for rest and relaxation with no need for accrual, flexible paid sick time with no need for accrual, 11 paid holidays, and other paid leaves, including up to 12 weeks of parental leave.

How to Apply: If interested, an application will need to be submitted online. Internal WGU employees will need to apply through the internal job board in Workday.

Additional Information

Disclaimer: The job posting highlights the most critical responsibilities and requirements of the job. It's not all-inclusive.

Accommodations: Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at recruiting@wgu.edu.

Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.


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